Remote Arrhythmia Detection for Eldercare in Malaysia

Area of Science:

• Biomedical Engineering
• Cardiology
• Digital Health

Background:

• Cardiovascular diseases are a leading cause of death globally, particularly in the elderly.
• Early detection and continuous monitoring of vital signs like electrocardiograms (ECG) are crucial for managing cardiovascular conditions.
• Remote patient monitoring offers improved accessibility and timely detection of abnormalities for elderly individuals.

Purpose of the Study:

• To design and deploy a scalable remote patient monitoring system for arrhythmia detection in elderly individuals.
• To develop and evaluate a novel two-phase classification scheme for improving ECG analysis.
• To assess the system's performance using real-world data and established databases.

Main Methods:

• Development of a scalable system architecture for near real-time ECG signal streaming.
• Implementation of a two-phase classification scheme to enhance existing ECG classification algorithms.
• Deployment of a prototype system at Sarawak General Hospital, collecting data from 27 patients.
• Evaluation using the MIT-BIH Arrhythmia Database and remotely collected single-lead ECG recordings.

Main Results:

• The developed system successfully supported remote streaming of ECG signals.
• The two-phase classification scheme demonstrated improved performance in arrhythmia detection.
• Evaluations confirmed the effectiveness of the classification scheme on both standard and remotely collected ECG data.

Conclusions:

• The designed remote patient monitoring system is effective for arrhythmia detection in the elderly.
• The proposed two-phase classification scheme significantly enhances ECG analysis performance.
• This approach holds promise for improving cardiovascular disease management and reducing mortality rates.